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Suggested confounders are: body mass index, socioeconomic status, physical fitness, smoking, medication use, age, gender and race (e.g. Armstrong et al. 2009; Portnoy et al. 2014; Scarpa et al. 2010).
Medication use, age, and current smoking status were similar among the four groups (all P > 0.05).
We identified several genes that showed group differences after controlling for concurrent psychotropic medication use, age, and depression severity.
Other significant covariates included psychoactive medication use, age 75 84 years, age 85+ years, worsened balance score, and chronic kidney disease (P < 0.05 for all).
Most studies were underpowered (that is, small sample sizes) and some failed to control for potential confounders such as medication use, age, sex, psychiatric comorbidity, stress coping/appraisal and abuse history.
We found no evidence of effect modification by PCBs or DDE, years of sport fish consumption, medication use, age, BMI, serum lipids, smoking, alcohol use, or steroid hormone levels.
Similar(53)
Finally, we attempted to classify diabetes as type 1, type 2, or other based on additional information including age at diagnosis, medication use, and age at birth of their last child (for females).
Recently, a systematic review showed that physical function, illness severity, cognition, comorbidity, presenting medical diagnosis, multiple medication use, and age could affect hospital length of stay (LOS), readmissions, discharge destination and mortality [ 16].
Of these measures, strength, maximal balance range, medication use, and age explained the largest proportions of the variance in 6MWD.
However, these studies could not disentangle the effects of ethnicity, medication use and age, which could have potentially confounded the results (Vancampfort et al. 2015).
The researchers used registry data and self-reports on asthma diagnosis and medication use since age 6 to identify asthma cases.
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